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AIF-C01 · Question #358

AIF-C01 Question #358: Real Exam Question with Answer & Explanation

The correct answer is B: Use a pre-trained deep learning model. Fine-tune the model on the dataset.. Fine-tuning a pre-trained deep learning model leverages transfer learning, reducing development effort because the model already captures general image features. Only minimal adjustments with the custom dataset are needed to achieve accurate classification.

Submitted by parkjh· Mar 30, 2026Modeling

Question

A company wants to classify images of different objects based on custom features extracted from a dataset. Which solution will meet this requirement with the LEAST development effort?

Options

  • AUse traditional ML algorithms with custom features extracted from the dataset.
  • BUse a pre-trained deep learning model. Fine-tune the model on the dataset.
  • CUse a generative adversarial network (GAN) model to classify the images.
  • DUse a support vector machine (SVM) with manually engineered features for classification.

Explanation

Fine-tuning a pre-trained deep learning model leverages transfer learning, reducing development effort because the model already captures general image features. Only minimal adjustments with the custom dataset are needed to achieve accurate classification.

Topics

#Image Classification#Deep Learning#Pre-trained Models#Fine-tuning

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